4 the relational data model and relational database constraints

Chapter 5

The Relational Data Model and

Relational Database Constraints

Chapter Outline

Relational Model Concepts

Relational Model Constraints and Relational

Database Schemas

Update Operations and Dealing with Constraint

Violations

The relational Model of Data is based on the concept of a

Relation

The strength of the relational approach to data management

comes from the formal foundation provided by the theory of

relations

We review the essentials of the formal relational model in

this chapter

In the formal relational model terminology:

a row is called a tuple

a column header is called an attribute

table is called a relation.

A Relation is a mathematical concept based on

the ideas of sets

The model was first proposed by Dr. E.F. Codd of

IBM Research in 1970 in the following paper:

"A Relational Model for Large Shared Data

Banks," Communications of the ACM, June 1970

The above paper caused a major revolution in the

field of database management and earned Dr.

Codd the coveted ACM Turing Award

Informal Definitions

Informally, a relation looks like a table of values.

A relation typically contains a set of rows.

The data elements in each row represent certain facts that correspond to a real-world entity or relationship

In the formal model, rows are called tuples

Each column has a column header that gives an indication of the meaning of the data items in that column In the formal model, the column header is called an attribute

name (or just attribute)

Example of a Relation

Informal Definitions

Key of a Relation:

Each row has a value of a data item (or set of items)

that uniquely identifies that row in the table

Called the key

In the STUDENT table, SSN is the key

Sometimes row-ids or sequential numbers are

assigned as keys to identify the rows in a table

Called artificial key or surrogate key

Formal Definitions - Schema

The Schema (or description) of a Relation:

Denoted by R(A1, A2, .....An)

R is the name of the relation

The attributes of the relation are A1, A2, ..., An

Degree (or arity) of a relation is the number of attributes n of

its relation schema

E.G: CUSTOMER (Cust-id, Cust-name, Address, Phone#)

CUSTOMER is the relation name

Defined over the four attributes: Cust-id, Cust-name,

Address, Phone#

Each attribute has a domain or a set of valid values.

For example, the domain of Cust-id is 6 digit numbers.

Formal Definitions - Tuple

A tuple is an ordered set of values (enclosed in angled

brackets „< … >‟)

Each value is derived from an appropriate domain.

A row in the CUSTOMER relation is a 4-tuple and would

consist of four values, for example:

<632895, "John Smith", "101 Main St. Atlanta, GA 30332",

"(404) 894-2000">

This is called a 4-tuple as it has 4 values

A tuple (row) in the CUSTOMER relation.

A relation is a set of such tuples (rows)

Formal Definitions - Domain

A domain has a logical definition:

Example: “USA_phone_numbers” are the set of 10 digit phone numbers valid in the U.S.

A domain also has a data-type or a format defined for it.

The USA_phone_numbers may have a format: (ddd)ddd-dddd where each d is a decimal digit.

Dates have various formats such as year, month, date formatted as yyyy-mm-dd, or as dd mm,yyyy etc.

The attribute name designates the role played by a domain in a relation:

Used to interpret the meaning of the data elements corresponding to that attribute

Example: The domain Date may be used to define two attributes named “Invoice-date” and “Payment-date” with different meanings

Formal Definitions - State

A relation state r of the relation schema R(A1,A2,., An) also denoted by r(R), is a set of n-tuples.

Each n-tuple t is an ordered list of n values tj = <v1,v2.. Vn>, where each value Vi, 1<=i<=n, is an element of dom(Ai) or is a special null value.

The relation state is a subset of the Cartesian product of the domains of its attributes

each domain contains the set of all possible values the attribute can take.

Example: attribute Cust-name is defined over the domain of character strings of maximum length 25

dom(Cust-name) is varchar(25).

Relation intension-schema R, relation extension- relation state r(R).

Formal Definitions - Summary

Formally,

Given R(A1, A2, .........., An)

r(R) dom (A1) X dom (A2) X ....X dom(An)

R(A1, A2, …, An) is the schema of the relation

R is the name of the relation

A1, A2, …, An are the attributes of the relation

r(R): a specific state (or "value" or “population”) of

relation R – this is a set of tuples (rows)

r(R) = {t1, t2, …, tn} where each ti is an n-tuple

ti = <v1, v2, …, vn> where each vj element-of dom(Aj)

Formal Definitions - Example

Let R(A1, A2) be a relation schema:

Let dom(A1) = {0,1}

Let dom(A2) = {a,b,c}

Then: dom(A1) X dom(A2) is all possible combinations:

{<0,a> , <0,b> , <0,c>, <1,a>, <1,b>, <1,c> }

The relation state r(R) dom(A1) X dom(A2)

For example: r(R) could be {<0,a> , <0,b> , <1,c> }

this is one possible state (or “population” or “extension”) r of

the relation R, defined over A1 and A2.

It has three 2-tuples: <0,a> , <0,b> , <1,c>

Definition Summary

Informal Terms Formal Terms

Table Relation

Column Header Attribute

All possible Column

Values

Domain

Row Tuple

Table Definition Schema of a Relation

Populated Table State of the Relation

Example – A relation STUDENT

Characteristics Of Relations

Ordering of tuples in a relation r(R):

The tuples are not considered to be ordered, even though they appear to be in the tabular form.

Ordering of attributes in a relation schema R (and of values within each tuple):

We will consider the attributes in R(A1, A2, ..., An) and the values in t=<v1, v2, ..., vn> to be ordered . (However, a more general alternative definition of

relation does not require this ordering).

Mapping from R to D.

Same state as previous Figure (but

with different order of tuples)

Values in a tuple:

All values are considered atomic (indivisible).

Each value in a tuple must be from the domain of

the attribute for that column

If tuple t = <v1, v2, …, vn> is a tuple (row) in the

relation state r of R(A1, A2, …, An)

Then each vi must be a value from dom(Ai)

A special null value is used to represent values

that are unknown or value exist but not available

or inapplicable to certain tuples.

Interpretation of a relation:

The relation schema can be interpreted as a

declaration or a type of assertion

Each tuple in the relation can then be interpreted as

a fact or a particular instance of the assertion

An alternative interpretation of a relation schema is

as a predicate ;in this case, the values in each tuple

are interpreted as values that satisfy the predicate.

Closed world assumption states that only true facts

in the universe are present within the extension of

the relation, any other combination of values makes

the predicate false

Relational Integrity Constraints

Constraints are conditions that must hold on all valid

relation states.

There are three main types of constraints in the relational

model:

Key constraints

Entity integrity constraints

Referential integrity constraints

Another implicit constraint is the domain constraint

Every value in a tuple must be an atomic value from the

domain of its attribute (or it could be null, if allowed for that

attribute)

Sub range of values from data type

Key Constraints

Superkey of R:

Is a set of attributes SK of R with the following condition:

No two tuples in any valid relation state r(R) will have the

same value for SK

That is, for any distinct tuples t1 and t2 in r(R), t1[SK] t2[SK]

This condition must hold in any valid state r(R)

Every relation has at least one default SK (set of all attributes)

Key of R:

A "minimal" superkey

That is, a key is a superkey K such that removal of any

attribute from K results in a set of attributes that is not a

superkey (does not possess the superkey uniqueness

property)

Key Constraints (continued)

Example: Consider the CAR relation schema:

CAR(State, Reg#, SerialNo, Make, Model, Year)

CAR has two keys:

Key1 = {State, Reg#}

Key2 = {SerialNo}

Both are also superkeys of CAR

{SerialNo, Make} is a superkey but not a key.

In general:

Any key is a superkey (but not vice versa)

Any set of attributes that includes a key is a superkey

A minimal superkey is also a key

Key Constraints (continued)

Relation schema may have more than one key, each key is called candidate key

If a relation has several candidate keys, one is chosen arbitrarily to be the primary key. The primary key attributes are underlined.

Example: Consider the CAR relation schema: CAR(State, Reg#, SerialNo, Make, Model, Year)

We chose SerialNo as the primary key

The primary key value is used to uniquely identify each tuple in a relation Provides the tuple identity

Also used to reference the tuple from another tuple General rule: Choose as primary key the smallest of the

candidate keys (in terms of size)

Not always applicable – choice is sometimes subjective

CAR table with two candidate keys –

LicenseNumber chosen as Primary Key

Relational Database Schema

Relational Database Schema:

„S‟ is a set of relation schemas that belong to the

same database S= {R1, R2, R3…} and a set of IC

S is the name of the whole database schema

R1, R2, …, Rn are the names of the individual

relation schemas within the database S

Relational database state DB={r1, r2, r3…}

A database state that does not obey all the

integrity constraints is called an invalid state, and a

state that satisfies all the constraints in IC is called

a valid state

COMPANY Database Schema

Entity Integrity

Entity Integrity:

The primary key attributes PK of each relation schema

R in S cannot have null values in any tuple of r(R).

This is because primary key values are used to identify the

individual tuples.

t[PK] null for any tuple t in r(R)

If PK has several attributes, null is not allowed in any of these

attributes

Note: Other attributes of R may be constrained to

disallow null values, even though they are not

members of the primary key.

Referential Integrity

A constraint involving two relations

The previous constraints involve a single relation.

Used to specify a relationship among tuples in

two relations:

The referencing relation and the referenced

relation.

Referential Integrity

Tuples in the referencing relation R1 have

attributes FK (called foreign key attributes) that

reference the primary key attributes PK of the

referenced relation R2.

A tuple t1 in R1 is said to reference a tuple t2 in

R2 if t1[FK] = t2[PK].

A referential integrity constraint can be displayed

in a relational database schema as a directed arc

from R1.FK to R2.

Referential Integrity (or foreign key)

Constraint

A set of attributes FK in relation schema R1 is a

foreign key of R1 that references relation R2 if it

satisfies the following two rules:

The attributes in FK have the same domain as the

primary key attributes PK of R2

A value of FK in a tuple t1 of the current state

r1(R1) either occurs as a value of PK for some

tuple t2 in the current state r2(R2) or is null

In case (2), the FK in R1 should not be a part of

its own primary key

a foreign key can refer to its own relation

Displaying a relational database

schema and its constraints

Each relation schema can be displayed as a row of attribute names

The name of the relation is written above the attribute names

The primary key attribute (or attributes) will be underlined

A foreign key (referential integrity) constraints is displayed as a directed arc (arrow) from the foreign key attributes to the referenced table

Can also point the the primary key of the referenced relation for clarity

Next slide shows the COMPANY relational schema diagram

Referential Integrity Constraints for COMPANY database

Other Types of Constraints

Semantic Integrity Constraints:

based on application semantics and cannot be

expressed by the model per se

Example: “the max. no. of hours per employee for

all projects he or she works on is 56 hrs per week”

A constraint specification language may have

to be used to express these

SQL-99 allows triggers and ASSERTIONS to

express for some of these

Populated database state

Each relation will have many tuples in its current relation

The relational database state is a union of all the

individual relation states

Whenever the database is changed, a new state arises

Basic operations for changing the database:

INSERT a new tuple in a relation

DELETE an existing tuple from a relation

MODIFY an attribute of an existing tuple

Next slide shows an example state for the COMPANY

database

Populated database state for COMPANY

Update Operations on Relations

INSERT a tuple.

DELETE a tuple.

MODIFY a tuple.

Integrity constraints should not be violated by the

update operations.

Several update operations may have to be

grouped together.

Updates may propagate to cause other updates

automatically. This may be necessary to maintain

integrity constraints.

Update Operations on Relations

In case of integrity violation, several actions can

be taken:

Cancel the operation that causes the violation

(RESTRICT or REJECT option)

Perform the operation but inform the user of the

violation

Trigger additional updates so the violation is

corrected (CASCADE option, SET NULL option)

Execute a user-specified error-correction routine

Possible violations for each operation

INSERT may violate any of the constraints:

Domain constraint:

if one of the attribute values provided for the new tuple is not

of the specified attribute domain

Key constraint:

if the value of a key attribute in the new tuple already exists in

another tuple in the relation

Referential integrity:

if a foreign key value in the new tuple references a primary key

value that does not exist in the referenced relation

Entity integrity:

if the primary key value is null in the new tuple

DELETE may violate only referential integrity:

If the primary key value of the tuple being deleted is

referenced from other tuples in the database

Can be remedied by several actions: RESTRICT, CASCADE,

SET NULL (see Chapter 8 for more details)

RESTRICT option: reject the deletion

CASCADE option: deleting tuples that reference the tuple that is

being delete.

SET NULL option: set the foreign keys of the referencing tuples

to NULL

One of the above options must be specified during

database design for each foreign key constraint

UPDATE may violate domain constraint and NOT NULL

constraint on an attribute being modified

Any of the other constraints may also be violated,

depending on the attribute being updated:

Updating the primary key (PK):

Similar to a DELETE followed by an INSERT

Need to specify similar options to DELETE

Updating a foreign key (FK):

May violate referential integrity

Updating an ordinary attribute (neither PK nor FK):

Can only violate domain constraints

Summary

Presented Relational Model Concepts

Definitions

Characteristics of relations

Discussed Relational Model Constraints and Relational

Database Schemas

Domain constraints‟

Key constraints

Entity integrity

Referential integrity

Described the Relational Update Operations and Dealing

with Constraint Violations

In-Class Exercise

(Taken from Exercise 5.20)

Consider the following relations for a database that keeps track of student

enrollment in courses and the books adopted for each course:

STUDENT(SSN, Name, Major, Bdate)

COURSE(Course#, Cname, Dept)

ENROLL(SSN, Course#, Quarter, Grade)

BOOK_ADOPTION(Course#, Quarter, Book_ISBN)

TEXT(Book_ISBN, Book_Title, Publisher, Author)

Draw a relational schema diagram specifying the foreign keys for this

schema.

In-Class Exercise

The schema of this question has the following four foreign keys:

1) The attribute SSN of relation ENROLL that references relation

STUDENT,

2) The attribute Course# in relation ENROLL that references

relation COURSE,

3) The attribute Course# in relation BOOK_ADOPTION that

references relation COURSE, and

4) The attribute Book_ISBN of relation BOOK_ADOPTION that

references relation TEXT.

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